Glift: Generic, efficient, random-access GPU data structures
Aaron E. Lefohn, Shubhabrata Sengupta, Joe Kniss, Robert Strzodka, John D. Owens
In ACM Transactions on Graphics, 25(1), January 2006.
Abstract: This article presents Glift, an abstraction and generic template library for defining complex, random-access graphics processor (GPU) data structures. Like modern CPU data structure libraries, Glift enables GPU programmers to separate algorithms from data structure definitions; thereby greatly simplifying algorithmic development and enabling reusable and interchangeable data structures. We characterize a large body of previously published GPU data structures in terms of our abstraction and present several new GPU data structures. The structures, a stack, quadtree, and octree, are explained using simple Glift concepts and implemented using reusable Glift components. We also describe two applications of these structures not previously demonstrated on GPUs: adaptive shadow maps and octree three-dimensional paint. Last, we show that our example Glift data structures perform comparably to handwritten implementations while requiring only a fraction of the programming effort.
Keyword(s): Adaptive, GPGPU, GPU, adaptive shadow maps, data structures, graphics hardware, multiresolution, octree textures, parallel computation
Article URL: http://doi.acm.org/10.1145/1122501.1122505
BibTeX format:
@article{Lefohn:2006:GGE,
  author = {Aaron E. Lefohn and Shubhabrata Sengupta and Joe Kniss and Robert Strzodka and John D. Owens},
  title = {Glift: Generic, efficient, random-access GPU data structures},
  journal = {ACM Transactions on Graphics},
  volume = {25},
  number = {1},
  pages = {60--99},
  month = jan,
  year = {2006},
}
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